Introduction:
One of the leading banks consulted us for designing an application which will provide facility to its customers to see the bill amount generated by their utility service provider, when they login into any home bank.
Background:
For the payment of utility service provider one had to login through the portal of the utility service provider after registering himself/herself and then pay the bill. In this process the customer not only had to remember the login process of utility service provider but also their bank details for processing the transaction. If the utility service provider details were made available in the home bank app itself then it would have become much simpler and easier.
Problem Statement:
Our task was to design an application which will get integrated to any home banking app for any utility service provider say electricity provider and make the customer experience seamless.
So when user logs in into the home banking app he/she must be able to see the bill amount of their respective utility service provider and make the payment their itself.
Methodology:
In the process of gathering data for our research on the utility service provider we found that initially the application was residing at their data center. We collected data pertaining to number of users logging to the utility service provider’s application and the number of users using home banking application to pay the bill.
Also we tried to do a comparative analysis of the cost incurred in the upkeep of the utility provider’s data center to that of a cloud service provider.
Analysis:
We analyzed the traffic of users per day to the utility service provider’s data center by doing log analysis for each month going back till two years. We found that average number of people loging were 400-500 daily and 10000 -15000 on a monthly basis.
Considering the low traffic of user on a per day basis of an utility service provider’s application having its own data center was proving costly. Here the requirement was less and the total cost incurred was approximately $40per person
Recommendation:
Considering the low traffic on their data center the utility service provider was recommended to migrate their application to cloud service. Not only the traffic could be easily handled by a cloud service but the cost incurred per person came down to $0.01.
Implementation:
In order to migrate the application we had to go through the 6 R’s of cloud migration to see if it could be rewritten. Out of the two option we had , one was to take the entire application with cloud into another cloud and other was to go complete serverless and convert it into lamda’s i.e to rewrite the business logic that won’t change for server considerably reducing the charge of service request. So we opted for the latter and decided to migrate the home banking application to be rewritten in lamda.
The advantage of doing this was that the expense of operations was reduced considerably. As local data center is expensive and migrating to cloud serverless architecture saved the time and money .
Challenges:
Some of the challenges we encountered were as follows:-
1. We had to exactly find out the count of user traffic per day by analyzing the logs by using the log processing query Splunk. Based on it the decision of effectiveness of cloud migration was taken.
2. As the code was already written we had to understand every single nuance of the code before migrating from one platform to another
3. For the mitigation we had an experienced team in Business logic and Java .IGNI business practice was followed.
4.When migrating application in a cloud data flows from one place to another .Our challenge was to make it hack proof, safe and secure. For this security challenge we wrote a custom route which will prevent certain hacks if if happens. For example in AWS million hacks happening can be prevented by custom firewall configuration. As a hacked small cURL command iterating for 20 days would genertte 7,20,000 calls leding to a condiderable cost . With AWS logging and alerting we did a custom configuration so that if 100 calls are seen in 5 minutes from the same IP then that IP gets blocked and send to AWS cloud watch.
5. We had to complete the migration in four weeks with holidays in between so we had planned well in advance and factored in unavailability of people during holidays and were able to complete it a week before than the expected date.
6.For the code deployment we had an expert experienced team in terraform and excellent knowledgeable Dev Ops team for seamless integration.
Conclusion:
Hence the Utility Service Provider Application was migtared from its data center to a AWS serverless architecture, integrating it with home banking application which reduced the cost significantly. The application was made hack proof with custom firewall configuration with the excellent expertise of our Dev Ops and terraform team.